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International Design and Test Workshop

作者： Nesrine Abid Tarek Ouni Kais Loukil Mohamed Abid Ahmed Chiheb Ammeri Laboratory of Computer and Embedded Systems National School of Engineering of Sfax TUNISIA MMA Laboratory National Institute of the Applied Sciences and Technologies Cartage university - TUNISIA

ISBN: (纸本)9781509049011

The covariance region descriptor has been proved robust in person detection application. However, detection is difficult to achieve on a serial processor. This is due to the large data set required to represent the image and the complex operations that need to be performed on the image. Multiprocessor systems (MPSoC) are usually adopted to speed up such application. In this paper, we propose a novel MPSoC architecture for fast person detection based on covariance descriptor. For this end, an optimized Khan Process Network parallel model of a covariance person detection application and the Sesame design and space exploration framework are used. Based on the optimal parallel model of covariance based person detection application, a multiprocessor architecture model is first proposed. These two models are modeled and validated using Sesame simulation. After that, the mapping of application tasks and channels on the architecture components is explored to define the optimal mapping architecture using execution time and platform cost. Results show that the six processors based architecture is the best when looking for the low computation cost and the four processors based architecture is the best when looking for the low cost.

关键词： computer architecture Computational modeling Tensile stress Space exploration Feature extraction Complexity theory Parallel processing

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Particle filter localization and real time obstacle avoidance control based on 3D perception for wheelchair mobile robot

Particle filter localization and real time obstacle avoidanc...

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International IEEE Conference on Intelligent systems, IS

作者： Emna Baklouti Nader Ben Amor Mohamed Jallouli Ecole Nationale d'Ingénieur de Sfax Université de Sfax Tunisie Computer & Embedded Systems Laboratory (CES)

Obstacle detection and localization behaviours have shown to work robustly in 2D perceived environment. With the progress of proximity sensors, precisely the emergence of 3D vision techniques, it would be interesting to examine these motion controllers whether for 3D perceived environment. 2D basic algorithms for obstacle avoidance or robot location, needs reformulation in order to process data from 3D perception devices. In this work, we introduce a 3D obstacle detection controller, combined with particle filter localization. The obstacle detection control described in this paper address 3D obstacles with different shapes and the particle filter uses 3D environment data to correct the wheelchair localization based on his kinematics model.

关键词： Three-dimensional displays Wheelchairs Robots Two dimensional displays Kinematics Collision avoidance Sensors

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A MapReduce-based parallel K-means clustering for large-scale CIM data verification

A MapReduce-based parallel K-means clustering for large-scal...

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作者： Deng, Chuang Liu, Yang Xu, Lixiong Yang, Jie Liu, Junyong Li, Siguang Li, Maozhen School of Electrical Engineering and Information Sichuan University Chengdu610065 China Department of Electronic and Computer Engineering Brunel University London UxbridgeUB8 3PH United Kingdom The Key Laboratory of Embedded Systems and Service Computing Tongji University Shanghai200092 China

The Common Information Model (CIM) has been heavily used in electric power grids for data exchange among a number of auxiliary systems such as communication systems, monitoring systems, and marketing systems. With a rapid deployment of digitalized devices in electric power networks, the volume of data continuously grows, which makes verification of CIM data a challenging issue. This paper presents a parallel K-means clustering algorithm for large-scale CIM data verification. The parallel K-means builds on the MapReduce computing model which has been widely taken up by the community in dealing with data-intensive applications. A genetic algorithm-based load-balancing scheme is designed to balance the workloads among the heterogeneous computing nodes for a further improvement in computation efficiency. The performance of the parallel K-means is initially evaluated in a small-scale in-house MapReduce cluster and subsequently evaluated in a commercial cloud computing platform. Finally, the parallel K-means is evaluated in large-scale simulated MapReduce environments. Both the experimental and simulation results show that the parallel K-means reduces the CIM data-verification time significantly compared with the sequential K-means clustering, while generating a high level of precision in data verification. Copyright © 2015 John Wiley & Sons, Ltd. Copyright © 2015 John Wiley & Sons, Ltd.

关键词： MapReduce

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Real time facial expression recognition app development on mobile phones

Real time facial expression recognition app development on m...

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International Conference on Fuzzy systems and Knowledge Discovery (FSKD)

作者： Humaid Alshamsi Hongying Meng Maozhen Li Dept. Electronic and Computer Engineering Brunel University London UK The Key Laboratory of Embedded Systems and Service Tongji University Shanghai China

ISBN: (纸本)9781509040940

Facial expression has made significant progress in recent years with many commercial systems are available for real-world applications. It gains strong interest to implement a facial expression system on a portable device such as tablet and smart phone device using the camera already integrated in the devices. It is very common to see face recognition phone unlocking app in new smart phones which are proven to be hassle free way to unlock a phone. Implementation a facial expression system in a smart phone would provide fun applications that can be used to measure the mood of the user in their daily life or as a tool for their daily monitoring of the motion in phycology studies. However, traditional facial expression algorithms are normally computing extensive and can only be implemented offline at a computer. In this paper, a novel automatic system has been proposed to recognize emotions from face images on a smart phone in real-time. In our system, the camera of the smart phone is used to capture the face image, BRIEF features are extracted and k-nearest neighbor algorithm is implemented for the classification. The experimental results demonstrate that the proposed facial expression recognition on mobile phone is successful and it gives up to 89.5% recognition accuracy.

关键词： Feature extraction Face recognition Databases Classification algorithms Smart phones Face Testing

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Sliding Mode and PI Controllers for Uncertain Flexible Joint Manipulator

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International Journal of Automation and computing 2015年第2期12卷 117-124页

作者： Lilia Zouari Hafedh Abid Mohamed Abid Computer and Embedded Systems Laboratory National School of Sfax EngineersUniversity of Sfax Laboratory of Sciences and Techniques of Automation (Lab-sta) National School of Sfax EngineersUniversity of Sfax

This paper is dealing with the problem of tracking control for uncertain flexible joint manipulator robots driven by brushless direct current motor(BDCM). Flexibility of joint in the manipulator constitutes one of the most important sources of uncertainties. In order to achieve high performance, all parts of the manipulator including actuator have been modeled. To cancel the tracking error, a hysteresis current controller and speed controllers have been developed. To evaluate the effectiveness of speed controllers, a comparative study between proportional integral(PI) and sliding mode controllers has been performed. Finally, simulation results carried out in the Matlab simulink environment demonstrate the high precision of sliding mode controller compared with PI controller in the presence of uncertainties of joint flexibility.

关键词： Flexible joint manipulator uncertainties proportional integral(PI) controller sliding mode brushless direct current motor.

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Continuous pain related behavior recognition from muscle activity and body movements

Continuous pain related behavior recognition from muscle act...

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International Conference on Fuzzy systems and Knowledge Discovery (FSKD)

作者： Rui Qin Hongying Meng Maozhen Li Dept. of Electronic and Computer Engineering Brunel University London Uxbridge UK The Key Laboratory of Embedded Systems and Service Tongji University Shanghai China

ISBN: (纸本)9781509040940

Chronic pain is a disease that the patients suffers a lot in their daily life and it is difficult to be released completely. It is difficult to manage because pain can come anytime and it is unpredictable. However, the pain can be represented by the pain related behaviors such as guiding and abrupt actions. In this paper, we will develop a machine learning based system that can detect the pain related behaviors from patient's Electromyography (EMG) signals and body movements continuously. The system includes data collection, feature extraction, modeling and classification. The data were collected using biosensor sensor for EMG and motion capture for body movement. Specific features are extracted from the body movement data. Then Random Forest and a Two Stage Classification (TSC) scheme (KNN coupled with Hidden Markov Model (HMM)) were used for pain related behavior detection in a continuous manner. The proposed method was tested on Emo-Pain corpus dataset provided by UCL and experimental results demonstrate the efficiency of the proposed method.

关键词： Pain Electromyography Radio frequency Hidden Markov models Trajectory Feature extraction Training

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Improvement of IOIOAI service for external sensors communication between app inventor and ioio

Improvement of IOIOAI service for external sensors communica...

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International Conference on Sciences and Techniques of Automatic Control and computer Engineering (STA)

作者： Slim Chtourou Mohamed Kharrat Nader Ben Amor Mohamed Jallouli Mohamed Abid Université de Sfax Computer & Embedded Systems CES laboratory Sfax Tunisia Université de Kairouan Institut Supérieur d'Informatique et de Gestion de Kairouan

ISBN: (纸本)9781509034086

Internet of Things (IoT) is currently leading the next world revolution. We witness more and more wearable devices and soon, all everyday objects will have a tiny computer. The ultimate objective of IoT is to leverage the technology abstraction as much as possible. Several fields are benefitting from the IoT revolution, among them we cite electronics, computer Science (CS) and education. There is a recent trend that focuses on developing HardWare (HW) or SoftWare (SW) solutions that facilitate the process of learning electronics and CS and can be integrated in the educational field. However, the existing solution focus on one of these sides and a combination of both HW & SW is quite rare. In this context, we present our developed solution that brings more simplification to the programming task for mobiles. It consists of an android service that links the features of the IOIO electrical board and the App Inventor android programming platform. This combination allows to user to develop Android apps that can control the IOIO board via Bluetooth and the board will interact with other electrical components connected to it. In this paper, we introduce the general overview of the system and present an improved version of the developed service that integrates support for additional commands to make App Inventor Apps capable of reading sensors connected to the IOIO board.

关键词： Androids Humanoid robots Pins Sensors Microprogramming Syntactics

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Methodology of embedded system design for underwater vehicle

Methodology of embedded system design for underwater vehicle

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IEEE SSD International Multi-Conference on systems, Signals and Devices

作者： Omar Triki Imen Hbiri Nouha Kchaou Hafedh Trabelsi Technopark of Sfax Digital Research Center of Sfax Sfax Tunisia Computer and Embedded Systems Laboratory University of Sfax Sfax Tunisia National School of Engineers of Sfax University of Sfax Sfax Tunisia

Underwater vehicles have developed greatly to the point that allowed their use in a variety of applications. However, using this kind of vehicles for in-service oil tank inspection is not yet advanced enough. As part of an effort to design a new class of underwater vehicles suitable for inspection, the present work ascertained requirements devoted to each component of those vehicles. A detailed design process was introduced and the main parts of the vehicle are described with emphasis on its related constraints. Finally, a control navigation strategy is proposed so that the vehicle will incorporate six degrees of freedom.

关键词： Inspection Robot sensing systems Vehicles Navigation Acoustics Service robots

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Cyber-physical Modeling and Control of Crowd of Pedestrians:A Review and New Framework

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IEEE/CAA Journal of Automatica Sinica 2015年第3期2卷 334-344页

作者： Kecai Cao Yangquan Chen Dan Stuart Dong Yue the College of Automation Nanjing University of Posts and Telecommunications Mechatronics Embedded Systems and Automation Laboratory School of EngineeringUniversity of California the Department of Electrical and Computer Engineering Utah State University

Recent advances in modeling and control of crowd of pedestrians are briefly surveyed in this paper. Possibilities of applying fractional calculus in the modeling of crowd of pedestrians have been shortly reviewed and discussed from different aspects such as descriptions of motion, interactions of long range and effects of memory. Control of the crowd of pedestrians have also been formulated using the framework of cyber-physical systems and been realized using networked Segways with onboard emergency response personnels to regulate the velocity and flux of the crowd. Platform for verification of the theoretical results are also provided in this paper. © 2014 Chinese Association of Automation.

关键词： Calculations embedded systems

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Adaptive Informative Sampling with Autonomous Underwater Vehicles: Acoustic versus Surface Communications

Adaptive Informative Sampling with Autonomous Underwater Veh...

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OCEANS MTS/IEEE Monterey (Conference)

作者： Stephanie Kemna David A. Caron Gaurav S. Sukhatme Robotic Embedded Systems Laboratory Computer Science Viterbi School of Engineering University of Southern California Caron Lab Department of Biological Sciences Dana and David Dornsife College of Letters Arts and Sciences University of Southern California

ISBN: (纸本)9781509015276

Autonomous underwater vehicles (AUVs) are cost-and time-effective platforms for mapping and monitoring of aquatic environments. Previous works have shown the benefits of using informative adaptive sampling approaches for field estimation over running standard surveys. We are interested in extending these works into decentralized multi-robot approaches. Simulation experiments with two AUVs, comparing no data sharing with timed surfacing for data sharing, show that the system performs better when data is shared. We further explore the trade-off between using high-bandwidth surface Wi-Fi communications, at the cost of surfacing, and low-bandwidth underwater acoustic communications (acomms). Our simulation results show that for multi-vehicle decentralized adaptive sampling, we can increase modeling performance by having vehicles share their measurements. Furthermore, zero loss acomms can perform better than data sharing through timed surfacing events. However, when acomms throughput is reduced, modeling uncertainty increases.

关键词： Vehicles Adaptation models Data models Sensors Path planning Biology Sea measurements

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